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| [net] | |
| # Testing | |
| #batch=1 | |
| #subdivisions=1 | |
| # Training | |
| batch=64 | |
| subdivisions=8 | |
| width=512 | |
| height=512 | |
| channels=3 | |
| momentum=0.949 | |
| decay=0.0005 | |
| angle=0 | |
| saturation = 1.5 | |
| exposure = 1.5 | |
| hue=.1 | |
| learning_rate=0.00261 | |
| burn_in=1000 | |
| max_batches = 500500 | |
| policy=steps | |
| steps=400000,450000 | |
| scales=.1,.1 | |
| #cutmix=1 | |
| mosaic=1 | |
| # ============ Backbone ============ # | |
| # Stem | |
| # 0 | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=32 | |
| size=3 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| # P1 | |
| # Downsample | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=64 | |
| size=3 | |
| stride=2 | |
| pad=1 | |
| activation=silu | |
| # Residual Block | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=32 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=64 | |
| size=3 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| # 4 (previous+1+3k) | |
| [shortcut] | |
| from=-3 | |
| activation=linear | |
| # P2 | |
| # Downsample | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=128 | |
| size=3 | |
| stride=2 | |
| pad=1 | |
| activation=silu | |
| # Split | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=64 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [route] | |
| layers = -2 | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=64 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| # Residual Block | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=64 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=64 | |
| size=3 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [shortcut] | |
| from=-3 | |
| activation=linear | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=64 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=64 | |
| size=3 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [shortcut] | |
| from=-3 | |
| activation=linear | |
| # Transition first | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=64 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| # Merge [-1, -(3k+4)] | |
| [route] | |
| layers = -1,-10 | |
| # Transition last | |
| # 17 (previous+7+3k) | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=128 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| # P3 | |
| # Downsample | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=256 | |
| size=3 | |
| stride=2 | |
| pad=1 | |
| activation=silu | |
| # Split | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=128 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [route] | |
| layers = -2 | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=128 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| # Residual Block | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=128 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=128 | |
| size=3 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [shortcut] | |
| from=-3 | |
| activation=linear | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=128 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=128 | |
| size=3 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [shortcut] | |
| from=-3 | |
| activation=linear | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=128 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=128 | |
| size=3 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [shortcut] | |
| from=-3 | |
| activation=linear | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=128 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=128 | |
| size=3 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [shortcut] | |
| from=-3 | |
| activation=linear | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=128 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=128 | |
| size=3 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [shortcut] | |
| from=-3 | |
| activation=linear | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=128 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=128 | |
| size=3 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [shortcut] | |
| from=-3 | |
| activation=linear | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=128 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=128 | |
| size=3 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [shortcut] | |
| from=-3 | |
| activation=linear | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=128 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=128 | |
| size=3 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [shortcut] | |
| from=-3 | |
| activation=linear | |
| # Transition first | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=128 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| # Merge [-1 -(4+3k)] | |
| [route] | |
| layers = -1,-28 | |
| # Transition last | |
| # 48 (previous+7+3k) | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=256 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| # P4 | |
| # Downsample | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=512 | |
| size=3 | |
| stride=2 | |
| pad=1 | |
| activation=silu | |
| # Split | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=256 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [route] | |
| layers = -2 | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=256 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| # Residual Block | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=256 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=256 | |
| size=3 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [shortcut] | |
| from=-3 | |
| activation=linear | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=256 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=256 | |
| size=3 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [shortcut] | |
| from=-3 | |
| activation=linear | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=256 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=256 | |
| size=3 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [shortcut] | |
| from=-3 | |
| activation=linear | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=256 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=256 | |
| size=3 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [shortcut] | |
| from=-3 | |
| activation=linear | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=256 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=256 | |
| size=3 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [shortcut] | |
| from=-3 | |
| activation=linear | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=256 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=256 | |
| size=3 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [shortcut] | |
| from=-3 | |
| activation=linear | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=256 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=256 | |
| size=3 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [shortcut] | |
| from=-3 | |
| activation=linear | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=256 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=256 | |
| size=3 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [shortcut] | |
| from=-3 | |
| activation=linear | |
| # Transition first | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=256 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| # Merge [-1 -(3k+4)] | |
| [route] | |
| layers = -1,-28 | |
| # Transition last | |
| # 79 (previous+7+3k) | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=512 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| # P5 | |
| # Downsample | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=1024 | |
| size=3 | |
| stride=2 | |
| pad=1 | |
| activation=silu | |
| # Split | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=512 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [route] | |
| layers = -2 | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=512 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| # Residual Block | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=512 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=512 | |
| size=3 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [shortcut] | |
| from=-3 | |
| activation=linear | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=512 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=512 | |
| size=3 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [shortcut] | |
| from=-3 | |
| activation=linear | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=512 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=512 | |
| size=3 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [shortcut] | |
| from=-3 | |
| activation=linear | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=512 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=512 | |
| size=3 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [shortcut] | |
| from=-3 | |
| activation=linear | |
| # Transition first | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=512 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| # Merge [-1 -(3k+4)] | |
| [route] | |
| layers = -1,-16 | |
| # Transition last | |
| # 98 (previous+7+3k) | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=1024 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| # ============ End of Backbone ============ # | |
| # ============ Neck ============ # | |
| # CSPSPP | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=512 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [route] | |
| layers = -2 | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=512 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [convolutional] | |
| batch_normalize=1 | |
| size=3 | |
| stride=1 | |
| pad=1 | |
| filters=512 | |
| activation=silu | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=512 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| ### SPP ### | |
| [maxpool] | |
| stride=1 | |
| size=5 | |
| [route] | |
| layers=-2 | |
| [maxpool] | |
| stride=1 | |
| size=9 | |
| [route] | |
| layers=-4 | |
| [maxpool] | |
| stride=1 | |
| size=13 | |
| [route] | |
| layers=-1,-3,-5,-6 | |
| ### End SPP ### | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=512 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [convolutional] | |
| batch_normalize=1 | |
| size=3 | |
| stride=1 | |
| pad=1 | |
| filters=512 | |
| activation=silu | |
| [route] | |
| layers = -1, -13 | |
| # 113 (previous+6+5+2k) | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=512 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| # End of CSPSPP | |
| # FPN-4 | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=256 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [upsample] | |
| stride=2 | |
| [route] | |
| layers = 79 | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=256 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [route] | |
| layers = -1, -3 | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=256 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| # Split | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=256 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [route] | |
| layers = -2 | |
| # Plain Block | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=256 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [convolutional] | |
| batch_normalize=1 | |
| size=3 | |
| stride=1 | |
| pad=1 | |
| filters=256 | |
| activation=silu | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=256 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [convolutional] | |
| batch_normalize=1 | |
| size=3 | |
| stride=1 | |
| pad=1 | |
| filters=256 | |
| activation=silu | |
| # Merge [-1, -(2k+2)] | |
| [route] | |
| layers = -1, -6 | |
| # Transition last | |
| # 127 (previous+6+4+2k) | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=256 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| # FPN-3 | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=128 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [upsample] | |
| stride=2 | |
| [route] | |
| layers = 48 | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=128 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [route] | |
| layers = -1, -3 | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=128 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| # Split | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=128 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [route] | |
| layers = -2 | |
| # Plain Block | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=128 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [convolutional] | |
| batch_normalize=1 | |
| size=3 | |
| stride=1 | |
| pad=1 | |
| filters=128 | |
| activation=silu | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=128 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [convolutional] | |
| batch_normalize=1 | |
| size=3 | |
| stride=1 | |
| pad=1 | |
| filters=128 | |
| activation=silu | |
| # Merge [-1, -(2k+2)] | |
| [route] | |
| layers = -1, -6 | |
| # Transition last | |
| # 141 (previous+6+4+2k) | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=128 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| # PAN-4 | |
| [convolutional] | |
| batch_normalize=1 | |
| size=3 | |
| stride=2 | |
| pad=1 | |
| filters=256 | |
| activation=silu | |
| [route] | |
| layers = -1, 127 | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=256 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| # Split | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=256 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [route] | |
| layers = -2 | |
| # Plain Block | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=256 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [convolutional] | |
| batch_normalize=1 | |
| size=3 | |
| stride=1 | |
| pad=1 | |
| filters=256 | |
| activation=silu | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=256 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [convolutional] | |
| batch_normalize=1 | |
| size=3 | |
| stride=1 | |
| pad=1 | |
| filters=256 | |
| activation=silu | |
| [route] | |
| layers = -1,-6 | |
| # Transition last | |
| # 152 (previous+3+4+2k) | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=256 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| # PAN-5 | |
| [convolutional] | |
| batch_normalize=1 | |
| size=3 | |
| stride=2 | |
| pad=1 | |
| filters=512 | |
| activation=silu | |
| [route] | |
| layers = -1, 113 | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=512 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| # Split | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=512 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [route] | |
| layers = -2 | |
| # Plain Block | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=512 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [convolutional] | |
| batch_normalize=1 | |
| size=3 | |
| stride=1 | |
| pad=1 | |
| filters=512 | |
| activation=silu | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=512 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| [convolutional] | |
| batch_normalize=1 | |
| size=3 | |
| stride=1 | |
| pad=1 | |
| filters=512 | |
| activation=silu | |
| [route] | |
| layers = -1,-6 | |
| # Transition last | |
| # 163 (previous+3+4+2k) | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=512 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=silu | |
| # ============ End of Neck ============ # | |
| # 164 | |
| [implicit_add] | |
| filters=256 | |
| # 165 | |
| [implicit_add] | |
| filters=512 | |
| # 166 | |
| [implicit_add] | |
| filters=1024 | |
| # 167 | |
| [implicit_mul] | |
| filters=255 | |
| # 168 | |
| [implicit_mul] | |
| filters=255 | |
| # 169 | |
| [implicit_mul] | |
| filters=255 | |
| # ============ Head ============ # | |
| # YOLO-3 | |
| [route] | |
| layers = 141 | |
| [convolutional] | |
| batch_normalize=1 | |
| size=3 | |
| stride=1 | |
| pad=1 | |
| filters=256 | |
| activation=silu | |
| [shift_channels] | |
| from=164 | |
| [convolutional] | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| filters=255 | |
| activation=linear | |
| [control_channels] | |
| from=167 | |
| [yolo] | |
| mask = 0,1,2 | |
| anchors = 12, 16, 19, 36, 40, 28, 36, 75, 76, 55, 72, 146, 142, 110, 192, 243, 459, 401 | |
| classes=80 | |
| num=9 | |
| jitter=.3 | |
| ignore_thresh = .7 | |
| truth_thresh = 1 | |
| random=1 | |
| scale_x_y = 1.05 | |
| iou_thresh=0.213 | |
| cls_normalizer=1.0 | |
| iou_normalizer=0.07 | |
| iou_loss=ciou | |
| nms_kind=greedynms | |
| beta_nms=0.6 | |
| # YOLO-4 | |
| [route] | |
| layers = 152 | |
| [convolutional] | |
| batch_normalize=1 | |
| size=3 | |
| stride=1 | |
| pad=1 | |
| filters=512 | |
| activation=silu | |
| [shift_channels] | |
| from=165 | |
| [convolutional] | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| filters=255 | |
| activation=linear | |
| [control_channels] | |
| from=168 | |
| [yolo] | |
| mask = 3,4,5 | |
| anchors = 12, 16, 19, 36, 40, 28, 36, 75, 76, 55, 72, 146, 142, 110, 192, 243, 459, 401 | |
| classes=80 | |
| num=9 | |
| jitter=.3 | |
| ignore_thresh = .7 | |
| truth_thresh = 1 | |
| random=1 | |
| scale_x_y = 1.05 | |
| iou_thresh=0.213 | |
| cls_normalizer=1.0 | |
| iou_normalizer=0.07 | |
| iou_loss=ciou | |
| nms_kind=greedynms | |
| beta_nms=0.6 | |
| # YOLO-5 | |
| [route] | |
| layers = 163 | |
| [convolutional] | |
| batch_normalize=1 | |
| size=3 | |
| stride=1 | |
| pad=1 | |
| filters=1024 | |
| activation=silu | |
| [shift_channels] | |
| from=166 | |
| [convolutional] | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| filters=255 | |
| activation=linear | |
| [control_channels] | |
| from=169 | |
| [yolo] | |
| mask = 6,7,8 | |
| anchors = 12, 16, 19, 36, 40, 28, 36, 75, 76, 55, 72, 146, 142, 110, 192, 243, 459, 401 | |
| classes=80 | |
| num=9 | |
| jitter=.3 | |
| ignore_thresh = .7 | |
| truth_thresh = 1 | |
| random=1 | |
| scale_x_y = 1.05 | |
| iou_thresh=0.213 | |
| cls_normalizer=1.0 | |
| iou_normalizer=0.07 | |
| iou_loss=ciou | |
| nms_kind=greedynms | |
| beta_nms=0.6 | |